Data & Analytics Solutions Architect - Ai Platforms, Aws, Databricks
Astra-North Infoteck Inc.
Data & Analytics Solutions Architect - AI platforms, AWS, DatabricksThe OpportunityWe are hiring a senior Data & Analytics Solutions Architect to lead the design of enterprise data, analytics, and AI platforms using AWS and Databricks. This role combines hands-on architecture, cloud modernization, data engineering, governance, technical leadership, and solution consulting. You will define architecture direction, guide implementation teams, and help organizations move from legacy environments to secure, scalable, production-ready platforms.
What You Will Do
Engage business and technology stakeholders to understand data, analytics, AI, cloud, and modernization requirements.
Define end-to-end architecture for AWS and Databricks-based data, analytics, and AI platforms.
Design secure, scalable, and high-performance Lakehouse solutions using AWS services, Databricks, Delta Lake, and Unity Catalog.
Architect data ingestion, integration, batch, streaming, data engineering, semantic, analytics, and AI solutions.
Design AI-enabled analytics experiences using Databricks Genie, semantic models, natural-language analytics, and governed data access.
Lead architecture definition, HLD/LLD preparation, non-functional assessments, migration planning, technical governance, and production readiness.
Establish standards for security, governance, metadata, lineage, observability, responsible AI, and DataOps delivery.
Lead data-platform modernization and cloud migration initiatives while addressing scalability, reliability, and compliance.
Conduct architecture reviews, identify risks and dependencies, and guide teams on practical mitigation strategies.
Drive performance, reliability, serverless-compute, and cost optimization across AWS and Databricks environments.
Support solutioning, RFP responses, effort estimation, technical presentations, and workshops.
Mentor architects and engineers and develop reusable accelerators, reference architectures, implementation frameworks, and best practices.
What You Bring
14+ years of experience in enterprise data architecture, AWS data platforms, Databricks, data engineering, and cloud modernization.
Hands-on expertise with AWS data services, Databricks, Databricks Genie, Unity Catalog, Delta Lake, Python, PySpark, and SQL.
Strong knowledge of the Databricks Data Intelligence Platform, including Databricks SQL, Workflows, Lakeflow, MLflow, serverless compute, and performance optimization.
Experience designing Lakehouse architectures, enterprise data platforms, data products, warehouses, semantic layers, and modern analytics solutions.
Expertise in ETL/ELT, batch and streaming integration, APIs, orchestration, data quality, metadata management, lineage, observability, and DataOps.
Experience implementing IAM/RBAC, encryption, privacy, masking, retention, auditability, governance, and responsible AI controls.
Experience supporting cloud transformation, architecture governance, RFPs, estimates, and client-facing solution discussions.
Understanding of financial services regulatory, security, privacy, resilience, and audit requirements.
Bachelor's degree in a relevant discipline. AWS, Databricks, data engineering, architecture, security, or AI/ML certifications are preferred.
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What You Will Do
Engage business and technology stakeholders to understand data, analytics, AI, cloud, and modernization requirements.
Define end-to-end architecture for AWS and Databricks-based data, analytics, and AI platforms.
Design secure, scalable, and high-performance Lakehouse solutions using AWS services, Databricks, Delta Lake, and Unity Catalog.
Architect data ingestion, integration, batch, streaming, data engineering, semantic, analytics, and AI solutions.
Design AI-enabled analytics experiences using Databricks Genie, semantic models, natural-language analytics, and governed data access.
Lead architecture definition, HLD/LLD preparation, non-functional assessments, migration planning, technical governance, and production readiness.
Establish standards for security, governance, metadata, lineage, observability, responsible AI, and DataOps delivery.
Lead data-platform modernization and cloud migration initiatives while addressing scalability, reliability, and compliance.
Conduct architecture reviews, identify risks and dependencies, and guide teams on practical mitigation strategies.
Drive performance, reliability, serverless-compute, and cost optimization across AWS and Databricks environments.
Support solutioning, RFP responses, effort estimation, technical presentations, and workshops.
Mentor architects and engineers and develop reusable accelerators, reference architectures, implementation frameworks, and best practices.
What You Bring
14+ years of experience in enterprise data architecture, AWS data platforms, Databricks, data engineering, and cloud modernization.
Hands-on expertise with AWS data services, Databricks, Databricks Genie, Unity Catalog, Delta Lake, Python, PySpark, and SQL.
Strong knowledge of the Databricks Data Intelligence Platform, including Databricks SQL, Workflows, Lakeflow, MLflow, serverless compute, and performance optimization.
Experience designing Lakehouse architectures, enterprise data platforms, data products, warehouses, semantic layers, and modern analytics solutions.
Expertise in ETL/ELT, batch and streaming integration, APIs, orchestration, data quality, metadata management, lineage, observability, and DataOps.
Experience implementing IAM/RBAC, encryption, privacy, masking, retention, auditability, governance, and responsible AI controls.
Experience supporting cloud transformation, architecture governance, RFPs, estimates, and client-facing solution discussions.
Understanding of financial services regulatory, security, privacy, resilience, and audit requirements.
Bachelor's degree in a relevant discipline. AWS, Databricks, data engineering, architecture, security, or AI/ML certifications are preferred.
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Vacancy posted 1 hour ago
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